AVP - Data Analyst

Accountabilities

1. Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification.
2. Execution of data cleansing and transformation tasks to prepare data for analysis.
3. Designing and building data pipelines to automate data movement and processing.
4. Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems.
5. Documentation of data quality findings and recommendations for improvement.

To be successful in this role, you should have:

1. Experience in Data Management, Data Governance including records management. Ability to review business processes from data lens and identify critical upstream and downstream components especially in financial services organisation – understanding of models, EUDAs etc.
2. Strong understanding of Data Governance, Data Quality & Controls, Data Lineage and Reference Data/Metadata Management including relevant policies and frameworks.
3. A clear understanding of the elements of an effective control environment, enterprise risk management framework, operational risk or other principal risk frameworks
4. Experience of managing stakeholders directly & indirectly and across geographies & cultures.
5. Strong understanding and practical exposure to application of BCBS 239 principles and related frameworks
6. Commercially astute, demonstrates a consultative, yet pragmatic approach with integrity to solving issues, focusing on areas of significance and value to the business.
7. A strong understanding of Risk and Control environment/control frameworks/op risk, including understanding of second and third line functions and impact across people, process and technology.
8. analytical techniques and tools to extract meaningful insights from complex data sets and drive data- Strategic Leadership: Provide strategic direction and leadership for data analysis initiatives, ensuring alignment with organizational and program goals. Functional understanding of financial crime and fraud data domains would be preferred.
9. Data Governance: Oversee data governance policies and procedures to ensure data integrity, security, and compliance with regulatory requirements.
10. Stakeholder Collaboration: Collaborate with cross-functional teams to identify data needs and deliver actionable insights.
11. Advanced Analytics: Utilize advanced driven decision-making
12. Deliver best in class insights to enable stakeholders to make informed business decisions and support data quality issue remediation.
13. Perform robust reivew and QA of key deliverables being sent out by the team to stakeholders
14. Demonstrate a collaborative communication style, promoting trust and respect with a range of stakeholders including Operational Risk/Chief Controls Office/ Chief Data Office/ Financial Crime Operations subject matter experts (SMEs), Chief Data Office, Risk Information Services, Technology

Some other desired skills include:

1. Graduate in any discipline
2. Effective communication and presentation skills.
3. Experience in Data Management/ Data Governance/ Data Quality Controls, Governance, Reporting and Risk Management preferably in a financial services organisation
4. Experience in Data Analytics and Insights (using latest tools and techniques e.g. Python, Tableau, Tableau Prep, Power Apps, Aletryx ), analytics on structured and unstructured data
5. Experience on data bases and data science/ analytics tools and techniques like SQL, AI and ML (on live projects and not just academic projects)
6. Proficient in MS Office – PPT, Excel, Word & Visio
7. Comprehensive understanding of Risk, Governance and Control Frameworks and Processes

Location - Noida

Purpose of the role

To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.